{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Jenia Golbstein - Ellipse Detection"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Download and extract dataset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Using TensorFlow backend.\n"
     ]
    }
   ],
   "source": [
    "%matplotlib inline\n",
    "# here we load all relevant essential libraries/function/classes for the following code to run  \n",
    "from utils_ellipse import *"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "dataset ='ellipse-dataset.tar.gz'\n",
    "\n",
    "Ellipse_Instance = ellipse(dataset, from_url = False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Some data visualizations"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>center_x</th>\n",
       "      <th>center_y</th>\n",
       "      <th>angle</th>\n",
       "      <th>axis_1</th>\n",
       "      <th>axis_2</th>\n",
       "      <th>Training_images</th>\n",
       "      <th>is_ellipse</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>9995</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>images/train/9995.jpg</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9996</th>\n",
       "      <td>30</td>\n",
       "      <td>22</td>\n",
       "      <td>321</td>\n",
       "      <td>6</td>\n",
       "      <td>10</td>\n",
       "      <td>images/train/9996.jpg</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9997</th>\n",
       "      <td>19</td>\n",
       "      <td>26</td>\n",
       "      <td>342</td>\n",
       "      <td>10</td>\n",
       "      <td>14</td>\n",
       "      <td>images/train/9997.jpg</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9998</th>\n",
       "      <td>31</td>\n",
       "      <td>17</td>\n",
       "      <td>52</td>\n",
       "      <td>17</td>\n",
       "      <td>21</td>\n",
       "      <td>images/train/9998.jpg</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9999</th>\n",
       "      <td>27</td>\n",
       "      <td>34</td>\n",
       "      <td>194</td>\n",
       "      <td>23</td>\n",
       "      <td>12</td>\n",
       "      <td>images/train/9999.jpg</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      center_x  center_y  angle  axis_1  axis_2        Training_images  \\\n",
       "9995         0         0      0       0       0  images/train/9995.jpg   \n",
       "9996        30        22    321       6      10  images/train/9996.jpg   \n",
       "9997        19        26    342      10      14  images/train/9997.jpg   \n",
       "9998        31        17     52      17      21  images/train/9998.jpg   \n",
       "9999        27        34    194      23      12  images/train/9999.jpg   \n",
       "\n",
       "     is_ellipse  \n",
       "9995      False  \n",
       "9996       True  \n",
       "9997       True  \n",
       "9998       True  \n",
       "9999       True  "
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_train, df_test = Ellipse_Instance.read_metadata()\n",
    "df_train.tail()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Add normalized angle column\n",
    "Convert angles to be in range of 0 to 179"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>center_x</th>\n",
       "      <th>center_y</th>\n",
       "      <th>angle</th>\n",
       "      <th>axis_1</th>\n",
       "      <th>axis_2</th>\n",
       "      <th>Training_images</th>\n",
       "      <th>is_ellipse</th>\n",
       "      <th>angle_norm</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>9995</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>images/train/9995.jpg</td>\n",
       "      <td>False</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9996</th>\n",
       "      <td>30</td>\n",
       "      <td>22</td>\n",
       "      <td>321</td>\n",
       "      <td>6</td>\n",
       "      <td>10</td>\n",
       "      <td>images/train/9996.jpg</td>\n",
       "      <td>True</td>\n",
       "      <td>141</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9997</th>\n",
       "      <td>19</td>\n",
       "      <td>26</td>\n",
       "      <td>342</td>\n",
       "      <td>10</td>\n",
       "      <td>14</td>\n",
       "      <td>images/train/9997.jpg</td>\n",
       "      <td>True</td>\n",
       "      <td>162</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9998</th>\n",
       "      <td>31</td>\n",
       "      <td>17</td>\n",
       "      <td>52</td>\n",
       "      <td>17</td>\n",
       "      <td>21</td>\n",
       "      <td>images/train/9998.jpg</td>\n",
       "      <td>True</td>\n",
       "      <td>52</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9999</th>\n",
       "      <td>27</td>\n",
       "      <td>34</td>\n",
       "      <td>194</td>\n",
       "      <td>23</td>\n",
       "      <td>12</td>\n",
       "      <td>images/train/9999.jpg</td>\n",
       "      <td>True</td>\n",
       "      <td>14</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      center_x  center_y  angle  axis_1  axis_2        Training_images  \\\n",
       "9995         0         0      0       0       0  images/train/9995.jpg   \n",
       "9996        30        22    321       6      10  images/train/9996.jpg   \n",
       "9997        19        26    342      10      14  images/train/9997.jpg   \n",
       "9998        31        17     52      17      21  images/train/9998.jpg   \n",
       "9999        27        34    194      23      12  images/train/9999.jpg   \n",
       "\n",
       "     is_ellipse  angle_norm  \n",
       "9995      False           0  \n",
       "9996       True         141  \n",
       "9997       True         162  \n",
       "9998       True          52  \n",
       "9999       True          14  "
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_train = Ellipse_Instance.add_normalized_angle(df_train)\n",
    "df_test = Ellipse_Instance.add_normalized_angle(df_test)\n",
    "df_train.tail()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Set axis_1 > axis_2 and modify the angle accordingly"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>center_x</th>\n",
       "      <th>center_y</th>\n",
       "      <th>angle</th>\n",
       "      <th>axis_1</th>\n",
       "      <th>axis_2</th>\n",
       "      <th>Training_images</th>\n",
       "      <th>is_ellipse</th>\n",
       "      <th>angle_norm</th>\n",
       "      <th>axis_1_new</th>\n",
       "      <th>axis_2_new</th>\n",
       "      <th>angle_norm_new</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>9995</th>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>images/train/9995.jpg</td>\n",
       "      <td>False</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9996</th>\n",
       "      <td>30</td>\n",
       "      <td>22</td>\n",
       "      <td>321</td>\n",
       "      <td>6</td>\n",
       "      <td>10</td>\n",
       "      <td>images/train/9996.jpg</td>\n",
       "      <td>True</td>\n",
       "      <td>141</td>\n",
       "      <td>10</td>\n",
       "      <td>6</td>\n",
       "      <td>51</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9997</th>\n",
       "      <td>19</td>\n",
       "      <td>26</td>\n",
       "      <td>342</td>\n",
       "      <td>10</td>\n",
       "      <td>14</td>\n",
       "      <td>images/train/9997.jpg</td>\n",
       "      <td>True</td>\n",
       "      <td>162</td>\n",
       "      <td>14</td>\n",
       "      <td>10</td>\n",
       "      <td>72</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9998</th>\n",
       "      <td>31</td>\n",
       "      <td>17</td>\n",
       "      <td>52</td>\n",
       "      <td>17</td>\n",
       "      <td>21</td>\n",
       "      <td>images/train/9998.jpg</td>\n",
       "      <td>True</td>\n",
       "      <td>52</td>\n",
       "      <td>21</td>\n",
       "      <td>17</td>\n",
       "      <td>142</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9999</th>\n",
       "      <td>27</td>\n",
       "      <td>34</td>\n",
       "      <td>194</td>\n",
       "      <td>23</td>\n",
       "      <td>12</td>\n",
       "      <td>images/train/9999.jpg</td>\n",
       "      <td>True</td>\n",
       "      <td>14</td>\n",
       "      <td>23</td>\n",
       "      <td>12</td>\n",
       "      <td>14</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      center_x  center_y  angle  axis_1  axis_2        Training_images  \\\n",
       "9995         0         0      0       0       0  images/train/9995.jpg   \n",
       "9996        30        22    321       6      10  images/train/9996.jpg   \n",
       "9997        19        26    342      10      14  images/train/9997.jpg   \n",
       "9998        31        17     52      17      21  images/train/9998.jpg   \n",
       "9999        27        34    194      23      12  images/train/9999.jpg   \n",
       "\n",
       "     is_ellipse  angle_norm  axis_1_new  axis_2_new  angle_norm_new  \n",
       "9995      False           0           0           0               0  \n",
       "9996       True         141          10           6              51  \n",
       "9997       True         162          14          10              72  \n",
       "9998       True          52          21          17             142  \n",
       "9999       True          14          23          12              14  "
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_train = Ellipse_Instance.set_ax1_bigger_than_ax2(df_train)\n",
    "df_test = Ellipse_Instance.set_ax1_bigger_than_ax2(df_test)\n",
    "df_train.tail()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Data distribution:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " is ellipse Training:\n",
      " Counter({'True': 6997, 'False': 3003})\n",
      " is ellipse Testing:\n",
      " Counter({'True': 688, 'False': 312})\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "Text(0.5,1,'Testing angles, 0 excluded')"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fb092783fd0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "print(' is ellipse Training:\\n',Counter(df_train[\"is_ellipse\"]))\n",
    "print(' is ellipse Testing:\\n',Counter(df_test[\"is_ellipse\"]))\n",
    "test_angles = df_test[\"angle\"].values\n",
    "train_angles = df_train[\"angle\"].values\n",
    "f = plt.figure(figsize=(16,4))\n",
    "f.add_subplot(121)\n",
    "plt.hist(train_angles[train_angles>0], 50);\n",
    "plt.title('Training angles, 0 excluded')\n",
    "f.add_subplot(122)\n",
    "plt.hist(test_angles[test_angles>0], 50);\n",
    "plt.title('Testing angles, 0 excluded')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fb0928b1eb8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# plot sampled dataframe rows\n",
    "plot_ellipse(df_train, 8, test=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Loading images, features and labels"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "X_train, train_features, y_train = Ellipse_Instance.get_data(df_train, use_norm_feat = True)\n",
    "X_test, test_features, y_test = Ellipse_Instance.get_data(df_test, use_norm_feat = True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Optional: image preprocessing, substracting backgroud and converting images to BW"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "155.0 155.0 155.0 +\\- 12.864198 12.737656 12.884564\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.image.AxesImage at 0x7fb092119860>"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fb09215b470>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "BW_train, BW_test = Ellipse_Instance.RGB2BW(X_train, X_test)\n",
    "plt.imshow(BW_train[5555,:,:])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Our data now contains BW images as well as RGB images.\n",
    "\n",
    "Let's preprocess the RGB images"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "X_train /= 255\n",
    "X_test /= 255"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Building a DL model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "__________________________________________________________________________________________________\n",
      "Layer (type)                    Output Shape         Param #     Connected to                     \n",
      "==================================================================================================\n",
      "input_8 (InputLayer)            (None, 50, 50, 3)    0                                            \n",
      "__________________________________________________________________________________________________\n",
      "first_conv (Conv2D)             (None, 50, 50, 32)   2432        input_8[0][0]                    \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_25 (BatchNo (None, 50, 50, 32)   128         first_conv[0][0]                 \n",
      "__________________________________________________________________________________________________\n",
      "second_conv (Conv2D)            (None, 46, 46, 32)   25632       batch_normalization_25[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "max_pooling2d_4 (MaxPooling2D)  (None, 23, 23, 32)   0           second_conv[0][0]                \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_26 (BatchNo (None, 23, 23, 32)   128         max_pooling2d_4[0][0]            \n",
      "__________________________________________________________________________________________________\n",
      "third_conv (Conv2D)             (None, 21, 21, 64)   18496       batch_normalization_26[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_27 (BatchNo (None, 21, 21, 64)   256         third_conv[0][0]                 \n",
      "__________________________________________________________________________________________________\n",
      "forth_conv (Conv2D)             (None, 19, 19, 64)   36928       batch_normalization_27[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_28 (BatchNo (None, 19, 19, 64)   256         forth_conv[0][0]                 \n",
      "__________________________________________________________________________________________________\n",
      "fifth_conv (Conv2D)             (None, 9, 9, 128)    32896       batch_normalization_28[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_29 (BatchNo (None, 9, 9, 128)    512         fifth_conv[0][0]                 \n",
      "__________________________________________________________________________________________________\n",
      "sixth_conv (Conv2D)             (None, 4, 4, 256)    131328      batch_normalization_29[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "global_average_pooling2d_4 (Glo (None, 256)          0           sixth_conv[0][0]                 \n",
      "__________________________________________________________________________________________________\n",
      "input_7 (InputLayer)            (None, 2500)         0                                            \n",
      "__________________________________________________________________________________________________\n",
      "dense_18 (Dense)                (None, 512)          131584      global_average_pooling2d_4[0][0] \n",
      "__________________________________________________________________________________________________\n",
      "dense_16 (Dense)                (None, 512)          1280512     input_7[0][0]                    \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_30 (BatchNo (None, 512)          2048        dense_18[0][0]                   \n",
      "__________________________________________________________________________________________________\n",
      "dense_17 (Dense)                (None, 64)           32832       dense_16[0][0]                   \n",
      "__________________________________________________________________________________________________\n",
      "concatenate_4 (Concatenate)     (None, 576)          0           batch_normalization_30[0][0]     \n",
      "                                                                 dense_17[0][0]                   \n",
      "__________________________________________________________________________________________________\n",
      "dense_19 (Dense)                (None, 256)          147712      concatenate_4[0][0]              \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_31 (BatchNo (None, 256)          1024        dense_19[0][0]                   \n",
      "__________________________________________________________________________________________________\n",
      "dense_20 (Dense)                (None, 256)          65792       batch_normalization_31[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "batch_normalization_32 (BatchNo (None, 256)          1024        dense_20[0][0]                   \n",
      "__________________________________________________________________________________________________\n",
      "features (Dense)                (None, 5)            1285        batch_normalization_32[0][0]     \n",
      "__________________________________________________________________________________________________\n",
      "ellipse (Dense)                 (None, 1)            513         batch_normalization_30[0][0]     \n",
      "==================================================================================================\n",
      "Total params: 1,913,318\n",
      "Trainable params: 1,910,630\n",
      "Non-trainable params: 2,688\n",
      "__________________________________________________________________________________________________\n"
     ]
    }
   ],
   "source": [
    "bw_input_shape = np.prod(BW_train.shape[1:])\n",
    "batch_size = 64\n",
    "hm_epochs = 20\n",
    "model = Ellipse_Instance.build_model(rgb_input_shape = X_train.shape[1:], \n",
    "                                     bw_input_shape = bw_input_shape, \n",
    "                                     feature_shape = train_features.shape[-1])\n",
    "\n",
    "# flatten BW images\n",
    "BW_test = BW_test.reshape([-1, bw_input_shape])\n",
    "BW_train = BW_train.reshape([-1, bw_input_shape])\n",
    "model.summary()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{0: 1.0, 1: 1.0}\n"
     ]
    }
   ],
   "source": [
    "# Specify whether you want to use class weights since the data is imbalanced\n",
    "# We don't really care of the features of the lines, we can set them to zero\n",
    "# if is_ellipse=0, So we want to penalize more \"mistakes\" in features when the image IS an ellipse\n",
    "# Therefore I've set the default to \"false\"\n",
    "\n",
    "use_class_weights = False\n",
    "\n",
    "if not use_class_weights:\n",
    "    class_weights = {0: 1., 1: 1.}\n",
    "else:\n",
    "    from sklearn.utils import class_weight\n",
    "    class_weights = class_weight.compute_class_weight('balanced', np.unique(y_train), y_train)\n",
    "    class_weights = {class_id : w for class_id, w in enumerate(class_weights)}    \n",
    "\n",
    "print(class_weights)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Train the model!"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Train on 6000 samples, validate on 4000 samples\n",
      "Epoch 1/20\n",
      "6000/6000 [==============================] - 13s 2ms/step - loss: 1.4504 - features_loss: 1346.6620 - ellipse_loss: 0.1038 - features_acc: 0.4937 - ellipse_acc: 0.9605 - val_loss: 14.2627 - val_features_loss: 3128.8609 - val_ellipse_loss: 11.1338 - val_features_acc: 0.0022 - val_ellipse_acc: 0.2973\n",
      "Epoch 2/20\n",
      "6000/6000 [==============================] - 7s 1ms/step - loss: 0.9774 - features_loss: 931.4950 - ellipse_loss: 0.0459 - features_acc: 0.4703 - ellipse_acc: 0.9850 - val_loss: 20.0173 - val_features_loss: 8662.0624 - val_ellipse_loss: 11.3552 - val_features_acc: 0.0000e+00 - val_ellipse_acc: 0.2955\n",
      "Epoch 3/20\n",
      "6000/6000 [==============================] - 7s 1ms/step - loss: 0.5761 - features_loss: 542.4648 - ellipse_loss: 0.0337 - features_acc: 0.5153 - ellipse_acc: 0.9887 - val_loss: 12.0877 - val_features_loss: 2570.0684 - val_ellipse_loss: 9.5177 - val_features_acc: 0.0440 - val_ellipse_acc: 0.3232\n",
      "Epoch 4/20\n",
      "6000/6000 [==============================] - 7s 1ms/step - loss: 0.2769 - features_loss: 244.6447 - ellipse_loss: 0.0323 - features_acc: 0.5620 - ellipse_acc: 0.9905 - val_loss: 1.4242 - val_features_loss: 723.9993 - val_ellipse_loss: 0.7002 - val_features_acc: 0.4945 - val_ellipse_acc: 0.8110\n",
      "Epoch 5/20\n",
      "6000/6000 [==============================] - 7s 1ms/step - loss: 0.1144 - features_loss: 95.7685 - ellipse_loss: 0.0186 - features_acc: 0.6155 - ellipse_acc: 0.9938 - val_loss: 10.1156 - val_features_loss: 1659.6734 - val_ellipse_loss: 8.4559 - val_features_acc: 0.1865 - val_ellipse_acc: 0.3493\n",
      "Epoch 6/20\n",
      "6000/6000 [==============================] - 7s 1ms/step - loss: 0.0760 - features_loss: 56.2182 - ellipse_loss: 0.0198 - features_acc: 0.6655 - ellipse_acc: 0.9935 - val_loss: 13.9006 - val_features_loss: 2886.9708 - val_ellipse_loss: 11.0137 - val_features_acc: 0.0220 - val_ellipse_acc: 0.2975\n",
      "Epoch 7/20\n",
      "6000/6000 [==============================] - 7s 1ms/step - loss: 0.0565 - features_loss: 42.2737 - ellipse_loss: 0.0143 - features_acc: 0.7593 - ellipse_acc: 0.9955 - val_loss: 11.4040 - val_features_loss: 1881.3880 - val_ellipse_loss: 9.5226 - val_features_acc: 0.0902 - val_ellipse_acc: 0.3167\n",
      "Epoch 8/20\n",
      "6000/6000 [==============================] - 7s 1ms/step - loss: 0.0387 - features_loss: 32.5443 - ellipse_loss: 0.0061 - features_acc: 0.7765 - ellipse_acc: 0.9987 - val_loss: 9.7376 - val_features_loss: 1503.2588 - val_ellipse_loss: 8.2344 - val_features_acc: 0.3757 - val_ellipse_acc: 0.3543\n",
      "Epoch 9/20\n",
      "6000/6000 [==============================] - 7s 1ms/step - loss: 0.0292 - features_loss: 25.0521 - ellipse_loss: 0.0042 - features_acc: 0.8005 - ellipse_acc: 0.9988 - val_loss: 3.1400 - val_features_loss: 891.8918 - val_ellipse_loss: 2.2481 - val_features_acc: 0.8932 - val_ellipse_acc: 0.7390\n",
      "Epoch 10/20\n",
      "6000/6000 [==============================] - 7s 1ms/step - loss: 0.0256 - features_loss: 23.0469 - ellipse_loss: 0.0025 - features_acc: 0.8140 - ellipse_acc: 0.9993 - val_loss: 2.3688 - val_features_loss: 654.4156 - val_ellipse_loss: 1.7144 - val_features_acc: 0.8828 - val_ellipse_acc: 0.7827\n",
      "Epoch 11/20\n",
      "6000/6000 [==============================] - 7s 1ms/step - loss: 0.0282 - features_loss: 24.7693 - ellipse_loss: 0.0034 - features_acc: 0.8217 - ellipse_acc: 0.9992 - val_loss: 1.5034 - val_features_loss: 653.0480 - val_ellipse_loss: 0.8504 - val_features_acc: 0.8670 - val_ellipse_acc: 0.8307\n",
      "Epoch 12/20\n",
      "6000/6000 [==============================] - 7s 1ms/step - loss: 0.0216 - features_loss: 19.4502 - ellipse_loss: 0.0021 - features_acc: 0.8063 - ellipse_acc: 0.9995 - val_loss: 2.2183 - val_features_loss: 579.7123 - val_ellipse_loss: 1.6385 - val_features_acc: 0.8788 - val_ellipse_acc: 0.7875\n",
      "Epoch 13/20\n",
      "6000/6000 [==============================] - 7s 1ms/step - loss: 0.0220 - features_loss: 19.1144 - ellipse_loss: 0.0029 - features_acc: 0.8258 - ellipse_acc: 0.9993 - val_loss: 0.5867 - val_features_loss: 327.2209 - val_ellipse_loss: 0.2595 - val_features_acc: 0.8660 - val_ellipse_acc: 0.9012\n",
      "Epoch 14/20\n",
      "6000/6000 [==============================] - 7s 1ms/step - loss: 0.0213 - features_loss: 19.0230 - ellipse_loss: 0.0023 - features_acc: 0.8112 - ellipse_acc: 0.9993 - val_loss: 1.3485 - val_features_loss: 523.4529 - val_ellipse_loss: 0.8250 - val_features_acc: 0.8800 - val_ellipse_acc: 0.8518\n",
      "Epoch 15/20\n",
      "6000/6000 [==============================] - 7s 1ms/step - loss: 0.0208 - features_loss: 20.0822 - ellipse_loss: 7.6666e-04 - features_acc: 0.8237 - ellipse_acc: 1.0000 - val_loss: 1.1075 - val_features_loss: 419.6038 - val_ellipse_loss: 0.6879 - val_features_acc: 0.8802 - val_ellipse_acc: 0.8505\n",
      "Epoch 16/20\n",
      "6000/6000 [==============================] - 7s 1ms/step - loss: 0.0198 - features_loss: 18.6860 - ellipse_loss: 0.0011 - features_acc: 0.8117 - ellipse_acc: 0.9998 - val_loss: 1.9155 - val_features_loss: 646.4011 - val_ellipse_loss: 1.2691 - val_features_acc: 0.8890 - val_ellipse_acc: 0.8017\n",
      "Epoch 17/20\n",
      "6000/6000 [==============================] - 7s 1ms/step - loss: 0.0188 - features_loss: 17.1355 - ellipse_loss: 0.0017 - features_acc: 0.8167 - ellipse_acc: 0.9993 - val_loss: 0.5691 - val_features_loss: 324.2363 - val_ellipse_loss: 0.2448 - val_features_acc: 0.8638 - val_ellipse_acc: 0.9427\n",
      "Epoch 18/20\n",
      "6000/6000 [==============================] - 7s 1ms/step - loss: 0.0189 - features_loss: 18.0133 - ellipse_loss: 8.8076e-04 - features_acc: 0.8263 - ellipse_acc: 0.9998 - val_loss: 0.2021 - val_features_loss: 188.6285 - val_ellipse_loss: 0.0135 - val_features_acc: 0.6325 - val_ellipse_acc: 0.9968\n",
      "Epoch 19/20\n",
      "6000/6000 [==============================] - 7s 1ms/step - loss: 0.0188 - features_loss: 17.7840 - ellipse_loss: 0.0011 - features_acc: 0.8300 - ellipse_acc: 0.9997 - val_loss: 2.7979 - val_features_loss: 732.2547 - val_ellipse_loss: 2.0656 - val_features_acc: 0.8878 - val_ellipse_acc: 0.7758\n",
      "Epoch 20/20\n",
      "6000/6000 [==============================] - 7s 1ms/step - loss: 0.0185 - features_loss: 17.8515 - ellipse_loss: 6.2764e-04 - features_acc: 0.8348 - ellipse_acc: 1.0000 - val_loss: 1.9198 - val_features_loss: 490.3357 - val_ellipse_loss: 1.4295 - val_features_acc: 0.8775 - val_ellipse_acc: 0.7967\n"
     ]
    }
   ],
   "source": [
    "model.compile(Adam(), loss=['mse', 'binary_crossentropy'], metrics=['accuracy'],\n",
    "             loss_weights=[.001, 1.])\n",
    "## callbacks:\n",
    "modelpath = 'ellipse_model.h5'\n",
    "checkpointer = ModelCheckpoint(filepath=modelpath, verbose=0, save_best_only=True)\n",
    "reduce_lr = ReduceLROnPlateau(monitor='val_features_loss', factor=0.5, patience=2, min_lr=0.00001)\n",
    "callbacks = [checkpointer, reduce_lr]\n",
    "\n",
    "history = model.fit([BW_train, X_train], [train_features, y_train], batch_size=batch_size, \n",
    "                             epochs=hm_epochs, verbose=1, validation_split=0.4, callbacks = callbacks,\n",
    "                             shuffle=True, class_weight=class_weights)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Plot training progress"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(0.3, 1.1)"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fb013982438>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "style.use('bmh')\n",
    "epochs = list(range(1, hm_epochs+1))\n",
    "val_ellipse_acc = history.history['val_ellipse_acc']\n",
    "val_features_acc = history.history['val_features_acc']\n",
    "ellipse_acc = history.history['ellipse_acc']\n",
    "features_acc = history.history['features_acc']\n",
    "\n",
    "f = plt.figure(figsize=(10,5));\n",
    "plt.plot(epochs, val_ellipse_acc, linewidth=4)\n",
    "plt.plot(epochs, val_features_acc, linewidth=4)\n",
    "plt.plot(epochs, ellipse_acc, linewidth=4)\n",
    "plt.plot(epochs, features_acc, linewidth=4)\n",
    "plt.xlabel('Epoch',fontsize=15), plt.ylabel('Accuracy',fontsize=15)\n",
    "legend = plt.legend(('val ellipse accuracy', 'val features accuracy', 'train ellipse accuracy', 'train features accuracy'))\n",
    "plt.setp(legend.get_texts(), color='k', fontsize=15);\n",
    "plt.ylim((0.3,1.1))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Evaluate model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1000/1000 [==============================] - 0s 436us/step\n",
      "Test Ellipse Accuracy 0.996\n",
      "Test Feature Accuracy 0.62\n"
     ]
    }
   ],
   "source": [
    "model.load_weights(modelpath)\n",
    "loss,feat_loss,ellip_loss,feat_acc,ellip_acc = model.evaluate([BW_test, X_test], [test_features, y_test])\n",
    "print('Test Ellipse Accuracy', ellip_acc)\n",
    "print('Test Feature Accuracy', feat_acc)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Plot Confusion Matrix For Test Ellipse Classification"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1000/1000 [==============================] - 1s 532us/step\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "Text(0.5,4.97309,'Predicted label')"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fb013610400>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "preds = model.predict([BW_test, X_test], verbose=1, batch_size=batch_size)\n",
    "preds_y = (preds[1].flatten()>0.5).astype(float);\n",
    "plt.figure(figsize=(7,5))\n",
    "\n",
    "cm = confusion_matrix(y_test, preds_y)\n",
    "plt.imshow(cm, interpolation='nearest', cmap=plt.cm.Blues)\n",
    "plt.title('Confusion matrix', fontsize=18)\n",
    "classes = ['Line', 'Ellipse']\n",
    "plt.colorbar()\n",
    "tick_marks = np.arange(len(classes));\n",
    "plt.xticks(tick_marks, classes, rotation=45,fontsize=11)\n",
    "plt.yticks(tick_marks, classes,fontsize=11)\n",
    "\n",
    "thresh = cm.max() / 2.\n",
    "for i, j in itertools.product(range(cm.shape[0]), range(cm.shape[1])):\n",
    "    plt.text(j, i, cm[i, j], horizontalalignment=\"center\", color=\"white\" if cm[i, j] > thresh else \"black\", fontsize=15)\n",
    "\n",
    "plt.tight_layout()\n",
    "plt.ylabel('True label',fontsize=14)\n",
    "plt.xlabel('Predicted label',fontsize=14)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Evaluate predicted ellipse features"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>angle</th>\n",
       "      <th>center_x</th>\n",
       "      <th>center_y</th>\n",
       "      <th>axis_1</th>\n",
       "      <th>axis_2</th>\n",
       "      <th>is_ellipse</th>\n",
       "      <th>Testing_images</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>75.0</td>\n",
       "      <td>32.0</td>\n",
       "      <td>24.0</td>\n",
       "      <td>21.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>True</td>\n",
       "      <td>images/test/0000.jpg</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>73.0</td>\n",
       "      <td>21.0</td>\n",
       "      <td>27.0</td>\n",
       "      <td>16.0</td>\n",
       "      <td>17.0</td>\n",
       "      <td>True</td>\n",
       "      <td>images/test/0001.jpg</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>False</td>\n",
       "      <td>images/test/0002.jpg</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>134.0</td>\n",
       "      <td>28.0</td>\n",
       "      <td>33.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>True</td>\n",
       "      <td>images/test/0003.jpg</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-0.0</td>\n",
       "      <td>False</td>\n",
       "      <td>images/test/0004.jpg</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   angle  center_x  center_y  axis_1  axis_2  is_ellipse        Testing_images\n",
       "0   75.0      32.0      24.0    21.0    15.0        True  images/test/0000.jpg\n",
       "1   73.0      21.0      27.0    16.0    17.0        True  images/test/0001.jpg\n",
       "2    0.0       0.0       1.0     0.0     0.0       False  images/test/0002.jpg\n",
       "3  134.0      28.0      33.0     6.0     4.0        True  images/test/0003.jpg\n",
       "4    0.0       1.0       0.0     0.0    -0.0       False  images/test/0004.jpg"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pred_features = np.round(preds[0])\n",
    "pred_features[pred_features<0] = 0\n",
    "df = pd.DataFrame()\n",
    "df['angle'] = pred_features[:,0]\n",
    "df['center_x'] = pred_features[:,1]\n",
    "df['center_y'] = pred_features[:,2]\n",
    "df['axis_1'] = pred_features[:,3]\n",
    "df['axis_2'] = pred_features[:,4]\n",
    "df['is_ellipse'] = np.bool8(preds_y)\n",
    "df['Testing_images'] = df_test[\"Testing_images\"].values\n",
    "df.to_csv('prediction.csv')\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(Text(0.5,0,'True normalized axis_2'),\n",
       " Text(0,0.5,'Predicted normalized axis_2'))"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7faffb0a4518>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "f = plt.figure(figsize=(15,15))\n",
    "f.add_subplot(321)\n",
    "plt.scatter(test_features[:,0], pred_features[:,0])\n",
    "plt.xlabel('True normalized angle'), plt.ylabel('Predicted normalized angle')\n",
    "f.add_subplot(322)\n",
    "plt.scatter(test_features[:,1], pred_features[:,1])\n",
    "plt.xlabel('True center_x'), plt.ylabel('Predicted center_x')\n",
    "f.add_subplot(323)\n",
    "plt.scatter(test_features[:,2], pred_features[:,2])\n",
    "plt.xlabel('True center_y'), plt.ylabel('Predicted center_y')\n",
    "f.add_subplot(324)\n",
    "plt.scatter(test_features[:,3], pred_features[:,3])\n",
    "plt.xlabel('True normalized axis_1'), plt.ylabel('Predicted normalized axis_1')\n",
    "f.add_subplot(325)\n",
    "plt.scatter(test_features[:,4], pred_features[:,4])\n",
    "plt.xlabel('True normalized axis_2'), plt.ylabel('Predicted normalized axis_2')"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.5.2"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
